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| Semester | Frühjahrsemester 2026 |
| Angebotsmuster | Jedes Frühjahrsem. |
| Dozierende | Aya Kachi (aya.kachi@unibas.ch, BeurteilerIn) |
| Inhalt | **Note** Those who completed 'Survey Research Methods' (the same course number #43494) in previous spring semesters cannot take this course for credit. This course introduces students to the quantitative empirical study of climate and sustainability policy using real-world data. Through hands-on exercises and guided analysis, students learn how to interpret, analyze, visualize, and communicate data on emissions, public opinion, and policy contexts. The course emphasizes the logic of empirical inference—that is, how quantitative evidence is generated, evaluated, and connected to policy debates. Students who need guidance also receive an introduction to statistical programming with R, the programming language used throughout the course. Building on foundational math and statistics typically covered in preparatory courses for Economics and other quantitative social sciences, the course offers a structured overview of descriptive, inferential, and predictive analysis, highlighting their purposes, underlying logic, and the statistical and visualization techniques required for rigorous application. Students work with a variety of data sources, including micro-data from surveys and survey experiments as well as country-level observational data. By the end of the course, students who engage consistently with the material will be able to critically assess data-based claims and conduct their own basic analyses of policy-relevant questions in the climate and sustainability domain. Beyond technical skills, the course is motivated by substantive questions that lie at the core of contemporary policy debates. For example, how are economic activity, greenhouse gas emissions, and climate policies distributed across countries, and why do these patterns matter for interpretation and comparison? How are climate policy opinions distributed within societies, and what do these distributions imply for policy communication, political feasibility, and policy design? Which countries have achieved larger emission reductions than others, and how do measurement choices shape these conclusions? More broadly, the course encourages students to reflect on when and how policies appear to work, and whether policy communication itself can meaningfully influence public attitudes. These questions serve as entry points for learning how quantitative methods support credible policy storytelling, rather than as ends in themselves. The instructor brings nearly 30 years of experience teaching and coaching on quantitative subjects, ranging from private math tutoring and PhD-level teaching assistantships to graduate-level instruction in applied data analysis. The course follows an inclusive teaching philosophy that aims to support students with diverse quantitative backgrounds, from those who completed an undergraduate degree in Economics with 'uneven' preparation to engaging master’s students seeking to strengthen their ability to analyze data and communicate policy-relevant insights using empirical evidence. |
| Lernziele | - Apply descriptive, inferential, and predictive analytical techniques to real-world data on climate and sustainability policy. - Use R to clean, analyze, model, and visualize data from surveys, experiments, and observational sources. - Critically evaluate quantitative evidence and communicate empirical findings in a clear, policy-relevant manner. - Understand the logic and process of data collection, especially for microdata such as surveys and survey experiments. |
| Literatur | - Sessions are accompanied by original handouts and datasets based on recent research. - Textbook: “Quantitative Social Science: And Introduction” by Kosuke Imai. ISBN: 9780691167039. (https://press.princeton.edu/books/hardcover/9780691167039/quantitative-social-science?srsltid=AfmBOorgzEQw2G_9P4zjALIWHe8N0plI6Yvl_rqlcBgFkSOn5Pkkelek ) - If you are unsure about your quant and programming skills, I recommend purchasing the above textbook even though some chapters (scanned) are available on ADAM. If you are already familiar with quant methods and R coding, feel free to turn to your favorite quant guidebooks for occasional support. |
| Bemerkungen | Students are asked to bring their own laptops. The course will be taught "in class" except the virtual first ("kick-off") session. |
| Weblink | Materials will be available here |
| Teilnahmevoraussetzungen | • Students should be comfortable with the math and statistics typically covered in undergraduate Economics, including summary statistics, basic probability, and the logic of simple regression and hypothesis testing. • No prior experience with R is required. However, if you have not used it before, please participate in the introductory R crash course offered by the Faculty of Business and Economics at the start of each semester. Information is available at: https://wwz.unibas.ch/en/computational-economics-and-finance/teaching/vorkurs-arbeiten-mit-wissenschaftlicher-software/ |
| Anmeldung zur Lehrveranstaltung | Registration: Please enroll in the Online Services (services.unibas.ch); Eucor-Students and mobility students of other Swiss Universities or the FHNW first have to register at the University of Basel BEFORE the start of the course and receive their login data by post (e-mail address of the University of Basel). Processing time up to a week! Detailed information can be found here: https://www.unibas.ch/de/Studium/Mobilitaet.html After successful registration you can enroll for the course in the Online Services (services.unibas.ch). Applies to everyone: Enrolment = Registration for the course and the exam! |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| unregelmässig | Siehe Einzeltermine | ||
| Datum | Zeit | Raum |
|---|---|---|
| Freitag 20.02.2026 | 14.15-16.00 Uhr | online per zoom, -- |
| Freitag 13.03.2026 | 14.15-18.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Seminarraum S13 HG.35 |
| Samstag 14.03.2026 | 10.15-14.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31 |
| Freitag 20.03.2026 | 14.15-18.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Seminarraum S15 HG.31 |
| Samstag 21.03.2026 | 10.15-14.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Auditorium |
| Freitag 27.03.2026 | 14.15-18.00 Uhr | Wirtschaftswissenschaftliche Fakultät, Auditorium |
| Module |
Modul: Erweiterung Gesellschaftswissenschaften M.A. (Master Studienfach: Politikwissenschaft) Modul: Interdisziplinäre Forschung zu Nachhaltigkeit (Masterstudium: Sustainable Development) Modul: Specific Electives in Finance, Controlling, Banking (Masterstudium: Wirtschaftswissenschaften) Modul: Specific Electives in Marketing and Strategic Management (Masterstudium: Wirtschaftswissenschaften) Modul: Technology Field (Masterstudium: Business and Technology) |
| Prüfung | Leistungsnachweis |
| Hinweise zur Prüfung | • Individual exercises (30 points) • Final assignment (40 points) • In-class group work & presentations (20 points) • Active participation (10 points) |
| An-/Abmeldung zur Prüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | Pass / Fail |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch |
| Anbietende Organisationseinheit | Wirtschaftswissenschaftliche Fakultät / WWZ |